In order to allow unmanned aerial vehicles (UAVs) to travel in civil unsegregated airspace, several technical problems must be solved. One of the most important issues is the “sense & avoid” problem: a UAV must be able to sense the presence of other aerial vehicles and, if necessary, perform an autonomous and safe last instant manoeuvre to avoid mid-air collision. Therefore, a UAV typically comprises an air collision avoidance system, sometimes also referred to as a Sense & Avoid system, including one or several sensors for sensing intruding aircraft, and collision avoidance functionality that uses the sensed data and the performance characteristics of the own aircraft to perform a safe escape manoeuvre. Since the collision avoidance system is a safety enhancing system it is crucial that the data supplied to the collision avoidance functionality are of high quality in order to avoid nuisance and unsafe maneuvers.
A crucial parameter in a collision avoidance system is the entity called Time To Collision (TTC) which, as the name implies, is the estimated time to impact with an intruding aircraft, calculated based on data regarding the own aircraft's position and motion and data on surrounding aerial vehicles, collected by the sensors of the collision avoidance system. The estimated TTC value is typically used to determine an entity sometimes called Time To Manoeuvre (TTM) which is an estimate of the time left before an escape manoeuvre must be performed in order to avoid a mid-air collision in a safe way. TTM is normally calculated as TTC minus a safety value, which safety value is determined based on, e.g., the performance characteristics of the own aircraft and the uncertainty associated with the estimated TTC value.
There are several known ways of estimating the time to collision with nearby aircrafts. For example, it is known to use cameras for capturing consecutive images of surrounding aircrafts such that the aircraft represent themselves as target points in the images, and estimate TTC based on the scale change in the target points from one image to another.
It is also well-known in the art to use different types of tracking filters adapted to estimate the time to collision with a nearby aircraft from a sequence of observations about the nearby aircraft's position, typically acquired by means of radar.
However, each of the above principles for estimating TTC suffer from drawbacks. The first principle according to which TTC estimates are calculated based on scale change in target points between consecutive images is only applicable when the intruding aircraft is very close to the own aircraft. The second principle according to which TTC estimates are estimated by a tracking filter suffers from the drawback that the uncertainty in the TTC estimates is high.